Machine learning enables computers to address problems by learning from data. Deep
learning is a type of machine learning that uses a hierarchical recombination of features to …

The rise and fall of artificial neural networks is well documented in the scientific literature of
both computer science and computational chemistry. Yet almost two decades later, we are …

Deep learning is becoming a standard tool in chemistry and materials science. Although
there are learning materials available for deep learning, none cover the applications in …

Deep learning models have demonstrated outstanding results in many data-rich areas of
research, such as computer vision and natural language processing. Currently, there is a …

Machine learning models are poised to make a transformative impact on chemical sciences
by dramatically accelerating computational algorithms and amplifying insights available from …

Computational Chemistry is currently a synergistic assembly between ab initio calculations,
simulation, machine learning (ML) and optimization strategies for describing, solving and …

QSAR. Despite this long tradition, machine learning methods gained substantial momentum
recently triggered by the success of deep learning in many application areas. 1 A wide …

The field of computational chemistry has seen a significant increase in the integration of
machine learning concepts and algorithms. In this Perspective, we surveyed 179 open …

Conspectus Recent advances in computer hardware and software have led to a revolution
in deep neural networks that has impacted fields ranging from language translation to …

In recent decades, artificial intelligence and machine learning have played a significant role
in increasing the efficiency of processes across a wide spectrum of industries. When it …